IT Ent. Data Architect

About Convene Inc. Convene, Inc. is a Tampa based, award-winning technology services organization with offices and resources throughout the US, Mexico, and India. We have successful, referenceable customers, competitive benefits, and high-growth opportunities.

Position Summary

• The IT Enterprise Data Architect defines, owns, and drives company enterprise data model across the internal corporate technology estate. This is a senior individual-contributor role centered on the purposeful, well-reasoned design of data repositories, canonical objects, classification schemes, and field-level mappings — including data as it moves through the Boomi integration layer.

The architect establishes the semantic and canonical data layers and the reusable data constructs that underpin the company's enterprise AI development, and sets the standards that data engineering, business applications, and integration teams build against.

• This is a hands-on architect — not solely a "drawer" of models: the individual is accountable for the blueprint and standards (the "what" and "why" of enterprise data) and is equally comfortable working directly in the data tools to profile, query, validate, and review data. They set standards while working in close partnership with the teams that build and operate the pipelines and platforms.

Reporting & Organizational Context

• Sits within:
  Internal IT
• Reports to Enterprise Architect
• Liaises with Product & Engineering (P&E) to ensure data alignment and interoperability — but is not responsible or accountable for the P&E / product data domain.
• Partners closely with Data Engineering and Information Security: both of which sit outside of IT, on pipeline/platform design and on data protection, classification, and compliance.
• Operates within and helps chair the Data Architecture Working Group: the cross-functional governance body (IT, P&E, Business) that owns the canonical model, ratifies design decisions, and sets the architecture standards the estate builds against.

Key Responsibilities

Enterprise Data Model & Architecture

• Own, define, and continuously evolve the enterprise data model spanning core corporate systems.
• Design data repositories, canonical objects, entity relationships, and the classification / taxonomy standards — with clear, documented rationale for each decision.
• Establish and govern field-level mapping standards across systems and through the integration layer.
• Define data domains, ownership, lineage, and reference / master-data approaches; drive consistency and reuse across the estate.

Semantic & Canonical Layers for Enterprise AI

• Define and maintain the semantic and canonical data layers that provide trustworthy, reusable data constructs for enterprise AI development and analytics.
• Design data structures that are "AI-ready" — supporting retrieval, grounding, feature engineering, and governed AI / ML use cases.
• Partner with Data Engineering and AI / automation teams to translate business concepts into consistent, well-defined semantic models.

Integration Architecture (Boomi)

• Architect the data flows and canonical mappings implemented through the Boomi integration layer; define integration patterns, data contracts, and reusable mapping standards.
• Ensure integrations preserve data integrity, classification, and lineage end-to-end.
• Provide design authority and hands-on guidance for how enterprise data is modeled and mapped within Boomi.

Mergers & Acquisitions (M&A) Data Integration

• Lead data mapping and integration for M&A activity — profiling acquired-company data, mapping it to the company s canonical model and integrating it into the enterprise data estate.
• Build repeatable playbooks, mapping templates, and integration patterns (e.g., through Boomi) that accelerate onboarding of acquired systems and data.
• Partner with Corporate Development, Data Engineering, and Information Security so acquired data is classified, protected, and reconciled throughout integration.

Platform Data Architecture

• Provide data architecture leadership for a highly customized Salesforce environment — custom objects, schema, and data model.
• Design and govern data structures within Snowflake as the enterprise data platform.
• Ext…